Orthogonal Frequency Division Multiplexing (OFDM) is the most widely used technique in modern communication systems today. OFDM not only provides a bandwidth efficient way of information transmission but it is also very effective in multipath fading in wireless communications. This is achieved in OFDM by dividing the main data stream into lower rate parallel streams each occupying its own sub-channel bandwidth without interfering with the others, and by the insertion of guard interval to absorb any channel dispersion. OFDM has been also attractive to provide the flexibility to choose digital modulation technique for its subcarriers to achieve power-bandwidth trade-offs in given channel conditions thus allowing adaptive modulation.
OFDM has equally found its applications in narrowband wireless systems such as Digital Radio Mondiale (DRM), Digital Audio Broadcast (DAB) and broadband system like WiMax, Digital Video Broadcast-Terrestrial (DVB-T), due to above mentioned features. In broadcast systems OFDM provides the key advantage of single frequency network (SFN), resulting in large bandwidth savings.
The performance of OFDM is very sensitive to carrier frequency and sampling clock offsets and very much dependent on the reliability and quality of the synchronization algorithms. It is therefore desirable to develop these synchronization algorithms to have optimum performance.
The DRM system provides reference pilot carriers (or cells as they are called in the standard itself) for the purpose of synchronization and equalization. FIG. 1 illustrates distribution of pilot cells and data cells for the robustness mode B. Gain reference cells occur scattered at successively different frequency positions (diagonals with dark dots in the figure). The scattered reference pilots are used for channel estimation while frequency reference pilots may be used for frequency synchronization. These frequency pilots as can be seen in FIG. 1 have a fixed-position in frequency domain (columns that are full with dark dots) and their location is independent of the robustness mode and the channel bandwidth. These pilots are also boosted in gain (compared to data cells) and their phase is chosen to provide continuous tones.
Frequency offset in OFDM system has two effects; first it attenuates and rotates data symbols at the output of FFT demodulator and the second, it destroys the orthogonality of the OFDM carriers resulting in Inter Channel Interference (ICI). The SNR degradation caused by ICI due to frequency offset has been studied and is given by FIG. 2. It can be seen that the frequency offset needs to be less than 1% of the carrier spacing to have a degradation of less than 0.5 dB at input SNR of 25 dB.
This condition puts very strict requirements on frequency synchronization algorithms, especially in consumer-oriented applications where carrier and clock frequencies may not only have large offsets but also larger fluctuations due to cheaper analog front ends.
Frequency synchronization for OFDM systems has been described by M. Speth et al in articles titled “Optimum Receiver Design for Wireless Broad-Band Systems Using OFDM—Part I/II”. IEEE Trans. Com., Vol. COM-47(11), 1668-1677, 1999 and IEEE Trans. Com., Vol. COM-49(4), 571-578, 2001. The algorithms studied by Speth et al for frequency synchronization for OFDM systems fall into pre and post FFT categories. Pre FFT algorithms are used for coarse estimation. Post FFT algorithms are used for fine tracking. The pre-FFT algorithms are time domain and are based on the cyclic prefix whereas post-FFT algorithms are in frequency domain. The performance of the time-domain guard interval based algorithms is generally not sufficient. For this reason these are used only for the coarse estimation. Switching between the pre and post FFT synchronization is based on some form of statistical information which may also result in burst errors due to occasional erroneous switching decisions.
This arrangement works well if the channel variations and RF front end phase noise is not causing rapid frequency variations. Usually this is the case in fixed wireless access for example. However in the mobile wireless applications with cheaper RF front ends and mobility this arrangement does not allow to compensate faster frequency variations (related to the RF Oscillator's PPM and phase noise). This is due to the fact that the post FFT frequency estimate is used in the long feedback loop for compensation as shown in the OFDM receiver structure proposed by Speth et al.
Use of frequency pilots for frequency acquisition using spectral estimation and correlation techniques has been described by V. Fisher et al in an article titled “Frequency Synchronization Strategy for a PC-based DRM Receiver”, published at the 7th International OFDM-Workshop (InOWo'02), Hamburg, 2002. However, these pilots have not been used for fine frequency tracking in the pre-FFT stage.
A method of frequency error detection in single carrier systems has been described by U. Mengali et al. in a book titled Synchronization Techniques for Digital Receivers. Plenum Press, 1997, pages 391-395 and in an article by L. Erup et al, titled “Interpolation in Digital Modems—Part II: Implementation and Performance IEEE Transaction on Communications, Vol. COM-41(6), 998-1008. 1993”. The frequency error of a frequency channel can be estimated from the product of the central signal strength in the channel and the difference between the signal strength in side bands on mutually opposite sides of the frequency channel. However this type of detector has not been suggested for frequency synchronization of OFDM signals.
In addition to the need for synchronization algorithms that have optimum performance, it is desirable that at the same time minimal computational effort is needed, to minimize power requirement for portable applications.
It is an object to provide for a synchronization process with optimum performance and at the same time with minimal computational effort.
A method is provided that comprises                sampling input samples from a received OFDM signal at successive time instants;        computing a Fourier transform of the input samples for a block of time instants;        computing a sliding Fourier transform at every new one of the input samples, using said successive input samples for time instants in the block to extract a pilot frequency tone;        detecting a frequency error signal from results of the sliding Fourier transform;        feeding back the detected frequency error signal in a frequency synchronization feedback loop.        
The Fourier transform of the block, which is conventional for OFDM reception, produces Fourier frequency components only after all of the input samples in the block have been processed. A DFT (Digital Fourier Transform) or FFT (Fast Fourier Transform) may be used. The sliding Fourier transform produces results at every new input sample, that is, earlier and more often than the Fourier transform of the block, successively using the new input samples for successive time instants in the block. This makes it possible to estimate rapid frequency estimations, at a time scale faster than the block duration. Frequency error detection results are used to synchronize a frequency with a feedback loop for fast frequency tracking. A Frequency Error Detector may be used that is based on the samples from sliding DFT estimates any variations in the carrier frequency of the input OFDM signal.
In an embodiment the samples are multiplied by a complex sinusoidal signal to rotate the data signals before Fourier transform of the block. A substantially sinusoidal signal may be used that is the result of approximation. A Taylor series approximation may be used for example. The sinusoidal signal is adapted in the feedback loop to track frequency variations in the samples. The sampling clock may also be synchronized by means of the frequency synchronization that uses the sliding Fourier transform, to track sample frequency offset. The feedback loop may be used to control a resampler or sample clock adjuster.
The sliding Fourier transform may be tuned to a pilot frequency tone in the OFDM signal. A pilot tone of a DRM signal may be used for example. In an embodiment a frequency error detector is used that computes a product of the sliding Fourier transform at successive time instants “n” for a central frequency “k” with a difference between the sliding Fourier transforms for the frequencies on mutually opposite sides of the central frequency. In an embodiment the central frequency and the frequencies on mutually opposite sides may be located at frequencies “k/N”, “(k−1)/N” and “(k+1)/N” wherein N is the window size of the sliding Fourier transform. The results of this computation for different time instants “n” may be used to control the complex substantially sinusoidal signal that is used to rotate the samples.
A plurality of groups of central and adjacent frequencies may be used, each for a different pilot tone. Two or three of such groups may be used for example. A sum of the frequency error detection results for the different groups may be used for frequency synchronization. This improves performance in the case of frequency selective fading channels.
The sliding Fourier transform may be implemented using successive application of a comb filter and a resonator to the input samples. When the sliding Fourier transform for a plurality of frequencies is used, the outputs of a single comb filter operation may be used as input for the resonators for all frequencies. In an embodiment the comb filter is configured to compute a difference between a current sample and a sample that has been delayed by a number of sampling periods N that defines a window size of the sliding Fourier transform filter. This results in a frequency response function with zeros at integer multiples of a base frequency that is inversely proportional to the window size N. In an embodiment the resonator for a frequency may be implemented using a feedback loop, wherein an output of the resonator is added to an input signal after applying phase shift factor exp(j*2*pi*k*n/N) to the output (herein k/N is the resonance frequency and n is the number of the sampling time instant for which the factor is applied). This results in a frequency response function with a pole at a frequency defined by the phase shift factor. The pole is made to coincide with one of the zeros of the comb filter, to produce an overall frequency response wherein this zero is cancelled.
In an embodiment a sample timing error is estimated from the decimated output of sliding Fourier transform of the first and second frequency pilots, achieved by multiplying a complex conjugate of the sliding Fourier transform for the first with the a complex conjugate of the sliding Fourier transform for the second frequency second frequency. An arctangent of the product may be computed to determine phase values from the product. Before taking the arctangent, may be summed to reduce the effect of noise. In an embodiment the feedback loop is configured to use only the products for selected decimated time instants that are M samples apart, wherein M is inversely proportional to a difference between the first and second frequencies. In this way, more complex computations to compensate for dependence of the result on the frequencies are avoided.
The computations may be implemented using a programmable computer, for example a signal processor, programmed to perform the required computations. The program may be supplied as a computer program product (e.g. on a semiconductor memory, a magnetic or optical disk, a modulated data signal) that carries instructions of the program.
Embodiment of the synchronization technique simplify the receiver architecture to avoid the need of switching. Only one algorithm suffices. The simplified receiver structure of this embodiment reduces the computational load significantly (no need to run two different algorithms simultaneously) and is therefore more suitable for low power portable applications.